{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "initial_id",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-08T09:52:47.287637Z",
     "start_time": "2024-06-08T09:52:46.348111Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "613252be66c5c97d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-08T09:53:28.061215Z",
     "start_time": "2024-06-08T09:53:28.039931Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Happiness.Rank</th>\n",
       "      <th>Happiness.Score</th>\n",
       "      <th>Whisker.high</th>\n",
       "      <th>Whisker.low</th>\n",
       "      <th>Economy..GDP.per.Capita.</th>\n",
       "      <th>Family</th>\n",
       "      <th>Health..Life.Expectancy.</th>\n",
       "      <th>Freedom</th>\n",
       "      <th>Generosity</th>\n",
       "      <th>Trust..Government.Corruption.</th>\n",
       "      <th>Dystopia.Residual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Norway</td>\n",
       "      <td>1</td>\n",
       "      <td>7.537</td>\n",
       "      <td>7.594445</td>\n",
       "      <td>7.479556</td>\n",
       "      <td>1.616463</td>\n",
       "      <td>1.533524</td>\n",
       "      <td>0.796667</td>\n",
       "      <td>0.635423</td>\n",
       "      <td>0.362012</td>\n",
       "      <td>0.315964</td>\n",
       "      <td>2.277027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>2</td>\n",
       "      <td>7.522</td>\n",
       "      <td>7.581728</td>\n",
       "      <td>7.462272</td>\n",
       "      <td>1.482383</td>\n",
       "      <td>1.551122</td>\n",
       "      <td>0.792566</td>\n",
       "      <td>0.626007</td>\n",
       "      <td>0.355280</td>\n",
       "      <td>0.400770</td>\n",
       "      <td>2.313707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>3</td>\n",
       "      <td>7.504</td>\n",
       "      <td>7.622030</td>\n",
       "      <td>7.385970</td>\n",
       "      <td>1.480633</td>\n",
       "      <td>1.610574</td>\n",
       "      <td>0.833552</td>\n",
       "      <td>0.627163</td>\n",
       "      <td>0.475540</td>\n",
       "      <td>0.153527</td>\n",
       "      <td>2.322715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>4</td>\n",
       "      <td>7.494</td>\n",
       "      <td>7.561772</td>\n",
       "      <td>7.426227</td>\n",
       "      <td>1.564980</td>\n",
       "      <td>1.516912</td>\n",
       "      <td>0.858131</td>\n",
       "      <td>0.620071</td>\n",
       "      <td>0.290549</td>\n",
       "      <td>0.367007</td>\n",
       "      <td>2.276716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Finland</td>\n",
       "      <td>5</td>\n",
       "      <td>7.469</td>\n",
       "      <td>7.527542</td>\n",
       "      <td>7.410458</td>\n",
       "      <td>1.443572</td>\n",
       "      <td>1.540247</td>\n",
       "      <td>0.809158</td>\n",
       "      <td>0.617951</td>\n",
       "      <td>0.245483</td>\n",
       "      <td>0.382612</td>\n",
       "      <td>2.430182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Netherlands</td>\n",
       "      <td>6</td>\n",
       "      <td>7.377</td>\n",
       "      <td>7.427426</td>\n",
       "      <td>7.326574</td>\n",
       "      <td>1.503945</td>\n",
       "      <td>1.428939</td>\n",
       "      <td>0.810696</td>\n",
       "      <td>0.585384</td>\n",
       "      <td>0.470490</td>\n",
       "      <td>0.282662</td>\n",
       "      <td>2.294804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Canada</td>\n",
       "      <td>7</td>\n",
       "      <td>7.316</td>\n",
       "      <td>7.384403</td>\n",
       "      <td>7.247597</td>\n",
       "      <td>1.479204</td>\n",
       "      <td>1.481349</td>\n",
       "      <td>0.834558</td>\n",
       "      <td>0.611101</td>\n",
       "      <td>0.435540</td>\n",
       "      <td>0.287372</td>\n",
       "      <td>2.187264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>New Zealand</td>\n",
       "      <td>8</td>\n",
       "      <td>7.314</td>\n",
       "      <td>7.379510</td>\n",
       "      <td>7.248490</td>\n",
       "      <td>1.405706</td>\n",
       "      <td>1.548195</td>\n",
       "      <td>0.816760</td>\n",
       "      <td>0.614062</td>\n",
       "      <td>0.500005</td>\n",
       "      <td>0.382817</td>\n",
       "      <td>2.046456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Sweden</td>\n",
       "      <td>9</td>\n",
       "      <td>7.284</td>\n",
       "      <td>7.344095</td>\n",
       "      <td>7.223905</td>\n",
       "      <td>1.494387</td>\n",
       "      <td>1.478162</td>\n",
       "      <td>0.830875</td>\n",
       "      <td>0.612924</td>\n",
       "      <td>0.385399</td>\n",
       "      <td>0.384399</td>\n",
       "      <td>2.097538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Australia</td>\n",
       "      <td>10</td>\n",
       "      <td>7.284</td>\n",
       "      <td>7.356651</td>\n",
       "      <td>7.211349</td>\n",
       "      <td>1.484415</td>\n",
       "      <td>1.510042</td>\n",
       "      <td>0.843887</td>\n",
       "      <td>0.601607</td>\n",
       "      <td>0.477699</td>\n",
       "      <td>0.301184</td>\n",
       "      <td>2.065211</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country  Happiness.Rank  Happiness.Score  Whisker.high  Whisker.low  \\\n",
       "0       Norway               1            7.537      7.594445     7.479556   \n",
       "1      Denmark               2            7.522      7.581728     7.462272   \n",
       "2      Iceland               3            7.504      7.622030     7.385970   \n",
       "3  Switzerland               4            7.494      7.561772     7.426227   \n",
       "4      Finland               5            7.469      7.527542     7.410458   \n",
       "5  Netherlands               6            7.377      7.427426     7.326574   \n",
       "6       Canada               7            7.316      7.384403     7.247597   \n",
       "7  New Zealand               8            7.314      7.379510     7.248490   \n",
       "8       Sweden               9            7.284      7.344095     7.223905   \n",
       "9    Australia              10            7.284      7.356651     7.211349   \n",
       "\n",
       "   Economy..GDP.per.Capita.    Family  Health..Life.Expectancy.   Freedom  \\\n",
       "0                  1.616463  1.533524                  0.796667  0.635423   \n",
       "1                  1.482383  1.551122                  0.792566  0.626007   \n",
       "2                  1.480633  1.610574                  0.833552  0.627163   \n",
       "3                  1.564980  1.516912                  0.858131  0.620071   \n",
       "4                  1.443572  1.540247                  0.809158  0.617951   \n",
       "5                  1.503945  1.428939                  0.810696  0.585384   \n",
       "6                  1.479204  1.481349                  0.834558  0.611101   \n",
       "7                  1.405706  1.548195                  0.816760  0.614062   \n",
       "8                  1.494387  1.478162                  0.830875  0.612924   \n",
       "9                  1.484415  1.510042                  0.843887  0.601607   \n",
       "\n",
       "   Generosity  Trust..Government.Corruption.  Dystopia.Residual  \n",
       "0    0.362012                       0.315964           2.277027  \n",
       "1    0.355280                       0.400770           2.313707  \n",
       "2    0.475540                       0.153527           2.322715  \n",
       "3    0.290549                       0.367007           2.276716  \n",
       "4    0.245483                       0.382612           2.430182  \n",
       "5    0.470490                       0.282662           2.294804  \n",
       "6    0.435540                       0.287372           2.187264  \n",
       "7    0.500005                       0.382817           2.046456  \n",
       "8    0.385399                       0.384399           2.097538  \n",
       "9    0.477699                       0.301184           2.065211  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"./data/world-happiness-report-2017.csv\")\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3065eaa0832b900b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import openpyxl as pyx\n",
    "wb = pyx.load_workbook(\"./data.xlsx\")\n",
    "sheet = wb.active"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b80ffab6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(<Cell 'Sheet1'.A1>, <Cell 'Sheet1'.B1>, <Cell 'Sheet1'.C1>, <Cell 'Sheet1'.D1>, <Cell 'Sheet1'.E1>, <Cell 'Sheet1'.F1>, <Cell 'Sheet1'.G1>, <Cell 'Sheet1'.H1>)\n"
     ]
    }
   ],
   "source": [
    "rows = sheet.rows\n",
    "for index in rows:\n",
    "    print(index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "693e6a84",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'class']\n"
     ]
    }
   ],
   "source": [
    "with open(\"../data/iris.csv\") as file:\n",
    "    first_line = file.readline()\n",
    "first_line = first_line.rstrip()\n",
    "title_list = first_line.split(\",\")\n",
    "print(title_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6de1fc87",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['1111']\n"
     ]
    }
   ],
   "source": [
    "str = \"1111\"\n",
    "print(str.split(\",\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8b12bd42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "range(0, 100)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "range(100)"
   ]
  }
 ],
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   "display_name": "Python 3",
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   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
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